Name
Abstract | ||
|---|---|---|
Co-location pattern mining, which discovers feature types that frequently appear in a nearby geographic region, plays an important role in spatial data mining. Common frameworks for mining co-location patterns generate numerous redundant patterns. Thus, several methods were proposed to overcome this drawback. However, most of these methods did not guarantee that the extracted co-location patterns were interesting for being generally based on statistical information. Thus, it is crucial to help the decision-maker choose interesting co-location patterns with an efficient interactive procedure. This paper proposed an interactive approach to discover interesting co-location patterns. First, ontologies were used to improve the integration of user knowledge. Second, an interactive process was designed to collaborate with the user to find interesting co-location patterns efficiently. Finally, a filter was designed to reduce the number of discovered co-location patterns in the result set further. The experimental results on both synthetic and real data sets demonstrated the effectiveness of our approach. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-55705-2_6 | DATABASE SYSTEMS FOR ADVANCED APPLICATIONS (DASFAA 2017) |
Keywords | Field | DocType |
Co-location pattern mining, Interactive, Ontology, Filter, Post-mining | Ontology (information science),Drawback,Ontology,Data mining,Data set,Result set,Computer science,Spatial data mining,User knowledge | Conference |
Volume | ISSN | Citations |
10179 | 0302-9743 | 2 |
PageRank | References | Authors |
0.36 | 9 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuguang Bao | 1 | 39 | 4.75 |
| Lizhen Wang | 2 | 153 | 26.16 |